Interpolation of a sequence of images using motion analysis

ABSTRACT

Two images are analyzed to compute a set of motion vectors that describes motion between the first and second images. A motion vector is computed for each pixel in an image at a time between the first and second images. This set of motion vectors may be defined at any time between the first and second images, such as the midpoint. The motion vectors may be computed using any of several techniques. An example technique is based on the constant brightness constraint, also referred to as optical flow. Each vector is specified at a pixel center in an image defined at the time between the first and second images. The vectors may point to points in the first and second images that are not on pixel centers. The motion vectors are used to warp the first and second images to a point in time of an output image between the first and second images using a factor that represents the time between the first and second image at which the output image occurs. The warped images are then blended using this factor to obtain the output image at the desired point in time between the first and second images. The point in time at which the output image occurs may be different from the time at which the motion vectors are determined. The same motion vectors may be used to determine two or more output images at different times between the first and second images. The images may be warped using a technique in which many small triangles are defined in an image corresponding in time to the point in time between the first and second images at which the motion vectors are determined. A transform for each small triangle from the point in time at which the motion vectors are determined to the desired interpolated image time is determined, e.g., the triangle is warped using the motion vectors associated with its vertices. For each pixel in each triangle in the output image, corresponding points in the first and second images are determined, and the first and second images are spatially sampled at these points. These samples for each pixel are combined to produce a value for that pixel in the output image. A motion vector map also may be generated between two fields of opposite field sense. An offset introduced by such calculation may be removed. During warping or other operation using the adjusted vector map, when sampling a field of one field sense to generate a field of an opposite field sense, that offset is reintroduced by translating the sampling region.

CROSS REFERENCE TO RELATED APPLICATION

This application claims the benefit under 35 U.S.C. 120 and is acontinuing application of U.S. patent application Ser. No. 09/657,699,filed Sep. 8, 2000, now pending, which is hereby incorporated byreference. This application also is related to U.S. patent applicationentitled “Analyzing Motion of Characteristics in Images,” by KatherineCornog and Randy Fayan, filed on even date herewith, and “CorrectingMotion Vector Maps for Image Processing,” by Katherine Cornog and RandyFayan, filed on even date herewith, both of which are herebyincorporated by reference.

BACKGROUND

For applications such as standards conversion and generation of slow andfast motion in film, television and other video productions, images in asequence of images may be simply repeated or dropped to achieve adesired sampling rate. Such a technique, however, generally producesunwanted visible artifacts such as jerky motion. Analysis of motion in asequence of images is commonly used to improve interpolation of thesequence of images.

Motion analysis generally is performed by determining a set of motionparameters that describe motion of pixels between a first image and asecond image. For example, the motion parameters may describe forwardmotion of pixels from the first image to the second image, and/orbackward motion of pixels from the second image to the first image. Themotion parameters may be defined at a time associated with either orboth of the first and second images or at a time between the first andsecond images. These motion parameters are then used to warp the firstand second images to obtain an interpolated image between the first andsecond images. This process generally is called motion compensatedinterpolation.

SUMMARY

Two images are analyzed to compute a set of motion vectors thatdescribes motion between the first and second images. A motion vector iscomputed for each pixel in an image at a time between the first andsecond images. This set of motion vectors may be defined at any timebetween the first and second images, such as the midpoint. The motionvectors may be computed using any of several techniques. An exampletechnique is based on the constant brightness constraint, also referredto as optical flow. Each vector is specified at a pixel center in animage defined at the time between the first and second images. Thevectors may point to points in the first and second images that are noton pixel centers.

The motion vectors are used to warp the first and second images to apoint in time of an output image between the first and second imagesusing a factor that represents the time between the first and secondimage at which the output image occurs. The warped images are thenblended using this factor to obtain the output image at the desiredpoint in time between the first and second images. The point in time atwhich the output image occurs may be different from the time at whichthe motion vectors are determined. The same motion vectors may be usedto determine two or more output images at different times between thefirst and second images.

The images may be warped using a technique in which many small trianglesare defined in an image corresponding in time to the point in timebetween the first and second images at which the motion vectors aredetermined. A transform for each small triangle from the point in timeat which the motion vectors are determined to the desired interpolatedimage time is determined, e.g., the triangle is warped using the motionvectors associated with its vertices. For each pixel in each triangle inthe output image, corresponding points in the first and second imagesare determined, and the first and second images are spatially sampled atthese points. These samples for each pixel are combined to produce avalue for that pixel in the output image.

Motion compensated interpolation also may be performed on two or moreimages that are dissimilar, or that are non-sequential, or that are notcontiguous in any one sequence of images. Thus, motion analysis may beused to process transitions between different sequences of images, suchas a dissolve or a jump cut. If two consecutive sequences of images havecorresponding audio tracks, the audio tracks may be processed toidentify a point in time at which motion compensated interpolation ofthe transition between the sequences should be performed.

Motion compensated interpolation of a sequence of images also may beperformed in conjunction with audio processing. For example, ifinterpolation of the sequence of images changes the duration of thesequence, the duration of a corresponding audio track may be changed toretain synchronization between the audio and the sequence of images.Resampling of the audio may be used to change the duration of the audio,but results in a change in pitch. Time scaling of the audio also may beused to change the duration of the audio without changing the pitch.

Occasionally, such interpolation creates visible artifacts in theresulting output images, particularly if there is a foreground objectthat occludes then reveals a background object, or if there is an objectthat appears or disappears in the images. In some cases, the foregroundmay appear to stretch or distort, or the background may appear tostretch or distort, or both. In such cases, a region in an image may bedefined. The region may be segmented into foreground and backgroundregions. A tracker then may be used to track either the foregroundregion or the background region or both as an object. A single motionvector or a parameterized motion model obtained from the tracker may beassigned to the tracked region. A combination map also may be defined tocontrol which pixels of the input images are used to contribute to eachpixel of an output image based on how a motion vector transforms a pixelfrom the input image to the output image.

For interlaced media, a vector map of motion also can be computedbetween fields of opposite sense, i.e., odd and even fields, by treatingthe two fields as if they are two images of the same type. The resultingvector map, when generated using two fields of opposite field sense, hasa vertical offset of about one half of a line. This vector map is thenmodified by adjusting the vertical component of all of the vectorseither up or down half a line. Warping operations then are performedusing the modified vector map. However, when sampling a field of onefield sense to generate a field of an opposite field sense, the samplingregion is translated either up or down half a line.

Accordingly, in one aspect, an output image associated with a point intime between a first image and a second image is generated bydetermining a motion vector for each pixel in an image at a map timebetween the first image and the second image, wherein the map time isdifferent from the point in time of the output image. Each motion vectordescribes motion of a pixel of the image at the map time to a firstpoint in the first image and a second point in the second image. Afactor that represents the point in time between the first image and thesecond image at which the output image occurs is calculated. The firstimage is warped according to the determined motion vectors and thefactor. The second image is warped according to the determined motionvectors and the factor. The warped first image and the warped secondimage are blended according to the factor to obtain the output image.

In another aspect, a plurality of output images, wherein each outputimage is associated with a different point in time between a first imageand a second image, is generated by determining a motion vector for eachpixel in an image at a map time between the first image and the secondimage. Each motion vector describes motion of a pixel of the image atthe map time to a first point in the first image and a second point inthe second image. For each output image, a factor that represents thepoint in time between the first image and the second image at which theoutput image occurs is calculated. For each output image, the firstimage is warped according to the determined motion vectors and thefactor for the output image. For each output image, the second image iswarped according to the determined motion vectors and the factor for theoutput image. For each output image, the warped first image and thewarped second image are blended according to the factor for the outputimage.

In one embodiment, the first image is in a first sequence of images andthe second image is in a second sequence of images such that the firstimage is not contiguous with the second image in a sequence of images.In another embodiment, the first sequence has associated audio and thesecond sequence has associated audio, the audio associated with thefirst sequence is dissolved to the audio associated with the secondsequence. In another embodiment, a combination of the output image andthe first and second images provides an output sequence of images with aduration at playback different from a duration of an input sequence ofimages containing the first and second images at playback. If the inputsequence of images has associated audio with a duration, the duration ofthe audio may be adjusted to match the duration of the output sequenceof images.

In one embodiment, the first and second images are processed to removeinvalid image data. In another embodiment, during warping of an image,any motion vector that transforms a point in the output image to an areaoutside of one of the first and second images results in no contributionfrom that input image to the output image. In another embodiment, theoutput image is initialized to a blend of the first and second imagesaccording to the determined factor.

In another aspect, a plurality of output images, wherein each outputimage is associated with a different point in time between a first imageof a first sequence of one or more images and a second image of a secondsequence of one or more images, is generated. For each output image, apair of a first image from the first sequence and a second image fromthe second sequence is selected. For each selected pair of first andsecond images, a motion vector is determined for each pixel in an imageat a map time between the first image and the second image, wherein themotion vector describes motion of a pixel of the image at the map timeto a first point in the first image and a second point in the secondimage. For each output image, a factor that represents the point intime, between the first and second images selected for the output image,at which the output image occurs is calculated. For each output image,the first image selected for the output image is warped according to thefactor for the output image and the motion vectors determined for thefirst and second images selected for the output image. For each outputimage, the second image selected for the output image is warpedaccording to the factor for the output image and the motion vectorsdetermined for the first and second images selected for the outputimage. For each output image, the warped first image and the warpedsecond image are blended according to the factor for the output image.

In another aspect, a transition of a plurality of output images isgenerated from a first sequence of images to a second sequence of imageswherein an image at an end of the first sequence is not contiguous withan image at a beginning of the second sequence. For each output image, apair of a first image from the first sequence and a second image fromthe second sequence is selected such that the output image has a pointin time between the first image and the second image in the transition.For each selected pair of first and second images, a set of motionvectors is determined that describes motion between the first image andthe second image. For each output image, a factor is calculated thatrepresents the point in time, between the first and second imagesselected for the output image, at which the output image occurs. Foreach output image, motion compensated interpolation is performed togenerate the output image according to the determined set of motionvectors and the calculated factor.

In another aspect, a jump cut is processed from a first image at an endof a first segment of sequence of images and corresponding audio and asecond image at a beginning of a second segment in the sequence ofimages and corresponding audio. The corresponding audio is processed toidentify an audio break between the audio corresponding to the firstsegment and the audio corresponding to the second segment. A set ofmotion vectors is determined that describes motion between the firstimage and the second image. Motion compensated interpolation isperformed to generate one or more images between the first image and thesecond image according to the determined set of motion vectors at apoint in time corresponding to the audio break.

In another aspect, a first image and a second image are warped andblended to obtain an output image at an output time between the firstimage and the second image. A set of motion vectors is determined at amap time and that describes motion between the first image and thesecond image. A primary transform is determined for each triangle in aset of triangles, defined in an image at the map time, from the map timeto the output time using the determined set of motion vectors. For eachtriangle, any pixels in the output image that are contained within thetriangle using the primary transform are identified. A first transformis determined for each triangle in the set of triangles from the outputtime to a time of the first image. For each pixel in each triangle atthe output time, a point in the first image is identified using thefirst transform and the first image is spatially sampled at the point. Asecond transform is determined for each triangle in the set of trianglesfrom the output time to a time of the second image. For each pixel ineach triangle at the output time, a point in the second image isidentified using the second transform and the second image is spatiallysampled at the point. For each pixel in each triangle at the outputtime, the spatially sampled first image and the spatially sampled secondimage are combined to obtain a value for the pixel in the output image.

In another aspect, a first image and a second image are warped to obtainan output image at an output time between the first image and the secondimage. A set of motion vectors is determined at a map time and thatdescribes motion between the first image and the second image. A primarytransform is determined for each triangle in a set of triangles, definedin an image at the map time, from the map time to the output time usingthe determined motion vectors. For each triangle, any pixels in theoutput image that are contained within the triangle at the output timeare identified using the primary transform. For each pixel in eachtriangle at the output time, the first image and the second image arespatially sampled at points corresponding to the pixel. The spatiallysampled first image and the spatially sampled second image are combinedto obtain a value for the pixel in the output image.

In one embodiment, the map time is between the first image and thesecond image. In another embodiment, the map time is different from theoutput time.

In another aspect, duration of an input sequence of images withassociated audio may be changed, wherein the input sequence of imagesand associated audio has a duration. An indication of a selection of anoperation by an operator, indicative of a desired duration of an outputsequence of images, is received. In response to the received indication,a first image and a second image in the sequence of images are selected.A set of motion vectors is determined that describes motion between thefirst image and the second image. Motion compensated interpolation isperformed to generate one or more images between the first image and thesecond image according to the determined motion vectors. Theseoperations are performed for multiple pairs of first and second imagesin the sequence of images to provide the output sequence of images. Theduration of the associated audio is adjusted to retain synchronizationwith the output sequence of images. In one embodiment, the outputsequence of images may be played back with the audio. In anotherembodiment, adjusting the duration of the audio involves resampling ofthe audio. In another embodiment, adjusting the duration of the audioinvolves time scaling of the audio.

In another aspect, color correction may be performed by generating afirst color histogram from first image from a first sequence of imagesand generating a second color histogram from a second image from asecond sequence of images. A set of motion vectors is determined fromthe first and second color histograms, that describes motion between thefirst color histogram and the second color histogram. A table of colorcorrection values is generated from the set of motion vectors. The tableof color correction values is applied to a sequence of images.

In another aspect, artifacts in an image created using motioncompensated interpolation of a first image and a second image may bereduced. A set of motion vectors is determined that describes motionbetween the first image and the second image. A foreground region and abackground region are identified in the first and second images.Tracking is performed on at least one of the foreground region and thebackground region to determine a motion model for the tracked region.The set of motion vectors corresponding to the tracked region is changedaccording to the motion model for the tracked region. Motion compensatedinterpolation is performed to generate one or more images between thefirst image and the second image according to the changed set of motionvectors. In one embodiment, a combination map is determined using thechanged set of motion vectors to indicate which of the first and secondimages are used to contribute to a pixel in an output image.

In another aspect, two fields of interlaced video may be processed bycomputing motion vectors describing motion of image characteristics froma field of a frame to another field of opposite field sense. An offsetcorresponding to one half of a line (having a sign according to anorientation of the y-axis of the image space and which field has the topline of the image) is removed from the motion vectors. The motionvectors then are used to generate a sampling region at a desired outputtime. The sampling region is transformed using the motion vectors to asample time at one of the fields. The sampling region also istransformed using the motion vectors to a sample time at the other ofthe fields. The field sense of an output field to be generated at thedesired output time is determined. The transformed sampling region forthe field with a field sense opposite the field sense of the outputfield is translated by an offset of one half of a line and having a signdetermined by the orientation of the y-axis of the image space and whichfield has the top line of the image. The output field is generated usingthe transformed and translated sampling regions and the fields of theframe. If the desired output time is the time of one of the fields, thegenerated output field may be combined with the field at the desiredoutput time to generate a progressive image. An effect may be performedon this progressive image. The progressive image with the effect may bevertically decimated (i.e., by sampling every other line) to produce afield at a desired output time.

In another aspect, two fields of interlaced video may be processed bycomputing motion vectors describing motion of image characteristics froma field of a frame to another field of opposite field sense. An offsetcorresponding to one half of a line and having a sign according to anorientation of the y-axis of the image space and which field includesthe top line. The time of one of the fields is selected as a desiredoutput time. A sampling region specified at the selected time istransformed using the motion vectors to a sample time at the field thatis being warped. The transformed sampling region is translated by anoffset of one half of a line and having a sign determined by theorientation of the y-axis of the image space and which field includesthe top line. The output field is generated at the desired output timeusing the transformed and translated sampling region and the field thatis being warped. The generated output field may be combined with thefield at the desired output time to generate a progressive image. Aneffect may be performed on this progressive image. The progressive imagewith the effect may be vertically decimated to produce a field at thedesired output time.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a data flow diagram of a process for generating aninterpolated image;

FIG. 2 is a data flow diagram of a process for estimating motion vectorsbetween two images;

FIGS. 3A-3G illustrate an implementation for manipulating a triangularmesh for performing a warping function using the motion vectors;

FIGS. 4A-B illustrate segmentation of an image region for modifying theset of motion vectors and creating a combination map;

FIG. 5A is a flowchart describing an approach for correcting a firstkind of artifact;

FIG. 5B is a flowchart describing an approach for correcting a secondkind of artifact;

FIG. 5C is a flowchart describing an approach for correcting a thirdkind of artifact;

FIG. 6 block diagram of an implementation for generating a set of imagesin a distributed manner;

FIG. 7 illustrates an example of a jump cut;

FIGS. 8A-8C illustrate an example of processing of a jump cut to addimages to a sequence around a jump cut;

FIG. 9 illustrates an example of processing a transition; and

FIG. 10 illustrates an example of generation of and effects processingon progressive images from interlaced images.

DETAILED DESCRIPTION

The general problem to solve using motion analysis to generate an imageis, given an image A[x, y] at time T_(A), and image B[x, y] at timeT_(B), calculate a new resultant image R[x, y] sampled at an arbitrarytime T_(R) between T_(A) and T_(B). For example, given images A[x, y] attime T_(A)=1, and image B[x, y] at time T_(B)=2 a new image R[x, y] maybe calculated that is a temporally “morphed” image at T_(R)=1.25. Usingthis technique for equally spaced time samples (e.g. 1.0, 1.2, 1.4, 1.8,and 2.0) results in a sequence of images that has smooth slow motion.Images may also be generated at unequally spaced samples to create aneffect of accelerating, decelerating, or even reverse motion over time.Any set of one or more points in time for interpolated samples may beused.

Referring now to FIG. 1, a data flow diagram of a process for generatingan interpolated image will now be described. Two images 100 and 102 areanalyzed by a motion vector generator 104 to produce a set of motionvectors, called a vector map 106, that includes a motion vector for eachpixel. Each motion vector describes motion of a pixel of an imagelocated at a time between the first image and the second image to apoint in the first image and a point in the second image. This time maybe different from the point in time of an output image to be generated.An example implementation of the motion vector generator 104 isdescribed in more detail below in connection to FIG. 2. The motionvectors are determined at a time between the times of the first imageand the second image, such as the midpoint. The image 100 and vector map106 are used by a warp engine 108 to produce a warped version of image100, as indicated at 110, at a desired point in time between the firstimage and the second image. Similarly, image 102 and the vector map 106are used by a warp engine 111 to produce a warped image 112 at a desiredpoint in time between the first image and the second image. An exampleimplementation of a warping engine is described in more detail inconnection with FIGS. 3A-3G. The images 110 and 112 are then blended byblender 114, according to the desired point in time between the firstimage and the second image. The blended image 116 is the desiredinterpolated image.

The blending function is defined by a blending factor, which representsthe point in time between the first image 100 and the second image 102at which the desired interpolated image is to occur. This blendingfactor is a value that is greater than or equal to 0, yet less than 1.In performing sample rate conversion, the desired interpolated image maybe assigned a point in time, and each existing image may be assigned apoint in time. This blending factor (d) may be calculated by quotient ofthe difference between the time T_(R) of the interpolated image and thetime T_(A) of the first image, and the difference between the time T_(B)of the second image and the time T_(A) of the first image, i.e.,d=(T_(R)−T_(A))/(T_(B)−T_(A)). When the first image 100 is processed bya warp engine 108, the blending factor (d) is used to scale the motionvectors which in turn are used to warp the image to the desired point.The second image 102, however, is warped by warp engine 110 using thedifference between 1 and the determined blending factor, i.e., (1−d) toscale the motion vectors. In contrast, the blender 114 scales the firstwarped image 110 by the difference between 1 and the blending factor(1−d). The warped second image 112 is scaled by the blending factor (d).

Referring now to FIG. 2, an example implementation of motion analysiswill now be described. There are many ways in which motion may beestimated between two images. Motion generally may be expressed by aparameterized motion model which may be translational, using twoparameters, affine, using six parameters, and projective, using eightparameters. These models are estimated by employing what is known as aconstant brightness constraint. Parameters are first estimated on areduced resolution image, then propagated to a higher resolution versionof the image. Details about implementations of such motion analysis maybe found in several references, including, but not limited to“Hierarchical Model-Based Motion Estimation,” by J. R. Bergen et al., inProceedings of Second European Conference on Computer Vision, pages237-252, Springer-Verlag, 1992; and “Hierarchical Model-Based Frame RateConverstion,” by J. R. Bergen et al, Technical Report, David SarnoffResearch Center, 1990; and “The Computation of Optical Flow, by S. S.Beauchemin and J. L. Barron, ACM Computing Surveys, Vol. 27, No. 3,September 1995, pp. 433-467, which are hereby incorporated by reference.

Motion analysis may be used to estimate a single motion vector for auser-defined region of an image, which is useful for stabilization andtracking applications. Motion analysis also may be used to estimate atranslational motion for every pixel in the image by using a smallregion, e.g., 5 pixels by 5 pixels, centered on each pixel as a regionfor estimation. This latter approach may be used for re-timing, such asa sample rate conversion, and morphing applications and is referred toas computing the “optical flow” between the images.

In general, the input used to compute optical flow is two images, forexample in RGB format. Other color representations also may be used. Theimages are converted from the existing format to a single component,typically the luminance component of YCrCb. However, other mappings fromthe color representation to a gray scale may be used. The computation ofoptical flow is based on an assumption that there is constant luminancefrom a first image to a second image and this assumption is used to findwhere each pixel moves. The result is a set of motion vectors, e.g., anarray of vertical and horizontal offsets (u and v), with a motion vectorfor each pixel. The offsets are fractional and thus may be stored in afixed or floating point format. The vectors are spatially aligned to thecenters of pixels in an image that represents a point in time betweenthe input images, such as the midpoint. A vector may describe the motionof a pixel of an image located at a time between the first image and thesecond image to a point in the first image and a point in the secondimage.

Most implementations of motion analysis transform a first image to thetime point of the second image in order to determine the residual motionerror at each level of estimation. Instead of warping one image toanother image across one time unit, in this implementation, each of thetwo images is warped to a center point in time, thus introducing lesserror and allowing a single set of motion parameters to represent themotion between the first and second images.

As can be seen in FIG. 2, calculation of optical flow thus uses severallevels of calculation using images at a different resolution at eachlevel. The number of levels (NumLevels) is related to the maximum amountof motion in an image that can be detected (MaxMotionDetected), inpixels per image. In particular,

MaxMotionDetected=2^((NumLevels−1)).

A suitable default number of levels for computing optical flow ofstandard definition images (720 by 486 pixels) is six. This number oflevels allows for detection of pixel motion of up to 32 pixels. More orfewer levels can be used depending on the spatial resolution of theimage and the expected maximum pixel motion.

Referring to FIG. 2, reduced resolution images 200 and 202 are used toestimate a a motion vector for each pixel or region as indicated at 204.The set of vectors so estimated may also be referred to as a “flowfield.” This estimated flow field is scaled up to a higher spatialresolution, as indicated at 206, and is applied to images 208 and 210 atthe higher resolution to obtain warped images 212 and 214. These warpedimages are used to estimate a flow field at this higher resolution asindicated at 216. The newly estimated flow field is combined with thescaled up flow field 206 as indicated at 218. The flow field at theintermediate resolution is scaled up again to a higher spatialresolution as indicated at 220. Images 222 and 224 at the higherresolution are warped using the scaled up flow field 220 to obtainwarped images 226 and 228. A flow field is estimated for the warpedimages as indicated at 230 and combined with the scaled up flow field220 as indicated at 232.

At each step of estimating a flow field, namely 204, 218 and 232,smoothing may be applied as indicated at 205, 219, and 233. Smoothingmay be performed based on the assumption that a pixel in an image movesin a similar way as any neighboring pixels. A smoothing technique thatmay be used is described, for example, in “Determining Optical Flow,” byB. K. P. Horn and B. G. Schunk, in Artificial Intelligence, Vol. 17,Nos. 1-3: pages 185-203, 1981, which is hereby incorporated byreference. Motion fields generally are not smooth at object boundaries.Thus, some smoothing techniques attempt to smooth only within objectsand not across strong gradient and motion boundaries. Some examples ofsuch smoothing techniques are found in “An Investigation of SmoothnessConstraints for the Estimation of Displacement Vector Fields from ImageSequences,” by H. H. Nagel and W. Enkelmann, in IEEE Transactions onPattern Analysis and Machine Intelligence, Vol. 8, No. 5, 1986, which ishereby incorporated by reference.

In areas where the spatial gradient is low it is not always possible toestimate the motion. For example, in the middle of a blank wall there isno local information that indicates if the wall is moving. In this casethe motion vectors for pixels that represent the middle of the blankwall are zero. Along strong unidirectional edges it is only possible toestimate the motion vector in the direction perpendicular to the edge,and result in a vector with only one independent component of motion.Areas which have sufficient spatial gradients in two directions containenough information to compute a reliable motion vector. The zero vectorsor the vectors with only one independent component of motion may beupdated at a different level in the computation of the optical flow, orthey may be modified by a post processing smoothing operation to moreaccurately reflect the true motion.

Referring now to FIGS. 3A-3G, an example implementation of warping afirst image and a second image to obtain an output image at an outputtime between the first and second images using a set of motion vectorswill now be described. A set of triangles is defined in an image at thepoint in time that corresponds to the set of motion vectors, thusdefining a mesh that covers that image. In this example, each trianglehas the area of one half of an image pixel. As shown in FIG. 3A, thevertices of each triangle are three pixels in the image. Vertex V1 hasthe coordinates x,y. Vertex V2 has the coordinates x+1,y. The vertex V3has the coordinates x,y+1. The arrows 400, 402 and 404 represent examplemotion vectors at the three pixel centers. Each triangle is then mappedto the time of the desired interpolated image, as shown in FIG. 3B, byadding the motion vectors of each vertex of the triangle, scaled by thefactor d, to the corresponding coordinates of each vertex of each shape.The pixels in the desired interpolated image, i.e., the output image,that are covered by the transformed triangle are then identified. In theexample shown in FIG. 3B, one pixel center V_(TR) is covered by thetransformed triangle. Similarly, each triangle is mapped to the time ofthe first image by adding the reverse motion vectors to the originalcoordinates of each vertex of the triangle, as shown in FIG. 3C.Similarly, each triangle is mapped to the time of the second image byadding the forward motion vectors to the original coordinates for eachvertex of each triangle. A transformation matrix from the time of thedesired interpolated image to the first image is then estimated for eachtriangle covering the output image. The matrix is estimated using thetwo input triangles. Each pixel contained in a triangle in the outputimage is transformed with the transformation matrix for the triangle toa point in the first image. This point often is not on a pixel center.The first image is then sampled at this point using, for example, aninterpolator such as a bilinear, bicubic or sinc filter, to obtain apixel value contribution from the first image. These steps are thenrepeated for the second image to obtain a pixel value contribution fromthe second image. The pixel contributions of the first and second imagesare blended, using the blending factor defined above, to obtain a valuefor the pixel in the desired output image, as indicated in FIG. 3E.

It might be observed from FIG. 3A, and as illustrated in FIG. 3F, twotriangles are associated with each pixel in the image at the timeassociated with the motion vectors. Both of these triangles aretransformed to the desired interpolated image, and checked to identifythe output pixels they cover. One triangle is formed at the upper leftcorner of a region defined by four pixels. Another triangle is formed inthe lower right of the region defined by the four pixels. It is possiblefor an output pixel center to fall exactly on an edge of a triangle. Inorder to address this case, a rule may be specified as to which outputpixels are defined to be included in which triangles. As an examplerule, as shown in FIG. 3G, the upper left triangle may be defined tohave two “inclusive” edges, V1, V2 and V1, V3. The lower right trianglemay be defined to have one inclusive edge, V2, V3. Points that land tothe right of or exactly on inclusive vertices and edges are consideredcovered by the triangle. Points that land to the left of or exactly onnoninclusive vertices and edges are considered not covered by thetriangle. For any given line segment, all tests of a point with respectto that line segment should be based on the same numerical calculation.In particular, a point is to the left of a line if it is not to theright of or on the line. Similarly, a point is to the right of a line,but not on it, if it is to the left of but not on the reversed line.

There are several variations, which may be made to the foregoing,including but not limited to the following.

Several modifications may be made to improve processing of interlacedimages. First, generating motion vectors between fields of interlacedvideo exhibits undesirable amounts of motion between the fields. Inorder to minimize the effects of the inherent field motion, each inputfield may be scaled up to a full height image before the motion vectorsare calculated, by using an interpolator such as bilinear, bicubic, orsinc interpolator. The motion vectors are then created on the scaled upfields, creating a frame-sized vector map. Second, when warpinginterlaced images using the techniques described above, only those linesthat contribute to the final output field are checked for inclusion in atriangle covering a portion of the output image. For instance, if an oddoutput field is being generated, only pixels on those lines thatcontribute to the odd field (either all the even lines, or all the oddlines) are checked for inclusion in each triangle.

In another embodiment, motion vectors can be computed between odd andeven fields of a frame by treating the two fields as if they are twoimages of the same type. The resulting vector map, such as vector map106 in FIG. 1, generated between two fields of opposite types, has avertical offset of about one half of a line. This vector map is thenmodified by adjusting the vertical component of all of the vectorseither up or down half a line. The warping and combining of the twofields is then performed using the modified vector map to generate anoutput field. The output field may be either an odd field or an evenfield. For example, an output field may be an even field generated atthe time of the odd field in order to create a progressive image at thetime of the odd field. The warping process is generally the same asdescribed above in connection with FIGS. 3A-3G, except that whensampling a field of one field sense to generate a field of an oppositefield sense, the offset removed from the vector map is reintroduced bytranslating the sampling region.

If the first image is an odd field and the second image is an evenfield, and the desired output image is an even field, then an offset isadded to the sampling region that samples the odd field.

If the first image is an odd field and the second image is an evenfield, and the desired output image is an odd field, then an offset isadded to the sampling region that samples the even field.

If the first image is an even field and the second image is an oddfield, and the desired output image is an even field, then an offset isadded to the sampling region that samples the odd field.

If the first image is an even field and the second image is an oddfield, and the desired output image is an odd field, then an offset isadded to the sampling region that samples the even field.

In each of these cases, the sampling region may be a triangle defined atthe time of the output field that is transformed to the times of theinput fields, as described above in connection with FIGS. 3C and 3D. Theoffset that is added to the sampling region is an offset of either onehalf line up or down that is added to each vertex of the triangle. Thesign of the offset depends on the orientation of the y-axis of the imagespace and which field has the top line of the image (in NTSC, the evenfield has the top line of the image), and whether the motion vectorsrepresent motion from the odd field to the even field or from the evenfield to the odd field. In particular, if the orientation of the y-axisis such that line numbers increase downward in the image, and the evenfield has the top line, then the offsets are defined by the followingtable:

Temporal field order Vertical for motion offset for Field Sense of FieldVertical offset to estimation vector map to be Generated sample regionvertices Odd field to −0.5 odd +0.5, when sampling even field even Oddfield to −0.5 even −0.5, when sampling even field odd Even field to +0.5odd +0.5, when sampling odd field even Even field to +0.5 even −0.5,when sampling odd field odd

By processing the interlaced images in this manner, progressive imagesmay be generated from interlaced images. Such progressive images may beused to improve effects processing. For example, as shown in FIG. 10,two input fields 1002 and 1004 are processed using optical flow motionestimation 1006 to produce a motion vector map. The second input field1004 is the warped using mesh warp engine 1008 to the time of field 1,as indicated at 1010. A field prior to the first field also may bewarped to the time of the first field and may be blended with the warpedsecond field to produce a field at the time of the first field. Thewarped second field and the first field are combined, as indicated at1012, to produce a progressive scan image 1014. This progressive scanimage could be used, for example, as a freeze frame image, an exportimage or as part of a sequence of progressive images, as indicated at1016. An effects processing module 1018 also may use this progressiveimage to perform various effects, such as a resizing operation. Theresults of the effects processing on the progressive image can bevertically decimated as indicated at 1020 (by taking only the odd linesor only the even lines) to generate an output field 1022.

Several modifications may be made to handle problems that arise aroundthe edges of the image. To reduce such problems, if the motion vectorsmap an output pixel to a point that lies outside of one of the originalinput images, no contribution is taken from the input image. Normally,both input images contribute to the output image. If a warped trianglecovers pixels in only one of the two input images, only that input imagecontributes to the output image. If neither input image is covered byone of the transformed triangles, neither input image contributes to theoutput pixels covered by that particular triangle.

To handle the case where certain output pixels have no contribution fromthe input images using the warping operation described above, beforethis operation is performed the two input images may be blended toproduce an output image using a standard alpha-blend function:R=(1−d)*A+d*B. When the warp operation is performed, if the input imagesdo not contribute anything to an output pixel, the output pixel stillhas a valid value.

Images that are captured from analog source video also may have pixelsaround the border of the image that are not part of the desired capturedimage. Often these pixels are black, including a black line at the topand bottom, and values ramping up from black along the left and rightedges. These edges may be handled specially so that they do notcontribute adversely to the motion vectors that are computed. The blacklines at the top and bottom of the image may be overwritten by thesecond line and the next to last line, respectively, before the motionvectors are computed. Likewise, the pixels at the left edge of each linemay be overwritten by the first valid (i.e., non-black) image pixel ineach line, and the pixels at the right edge of each line may beoverwritten by the last valid image pixel in each line. When generatingthe output image, the left and right edge output pixels are taken fromthe original image, with all other pixels being produced by the warpingoperation.

Occasionally, there are regions in an image in which motion of pixelscannot be estimated correctly by computing optical flow. These regionsmay be identified by the occurrence of a high level of error thatremains when the two input images are warped toward each other, to thesame point in time. This error can be estimated by subtracting the firstwarped image from the second warped image, to produce a differenceimage. In this difference image, areas containing large non-zero valuesmay be aggregate into regions, for example by using a thresholdoperation. A morphological hole fill operator may be used to unify smallgroups of error pixels into contiguous regions.

Non-zero areas in the difference image correspond to areas where themotion vectors do not correctly predict the motion and/or areas in whichthe constant brightness constraint, the assumption behind thecomputation of optical flow, is violated. One such violation commonlyoccurs when objects enter or leave the scene, or are revealed oroccluded. When such a violation of the constant brightness constraintoccurs, the motion vectors from one coherent area of motion bleed intoanother coherent area of motion. When these motion vectors are used towarp the input images to produce an output image, the output image hasvisible artifacts.

Referring now to FIG. 4A, to account for violations of the constantbrightness constraint, a region of an image that contains an artifact issegmented. The image region is segmented into two coherently movingareas: a foreground region (FG1 and FG2) and a background region (BG).This segmentation is performed on each input image of each pair of inputimages for which the output image exhibits a visible artifact.Identification of a region and this segmentation may be performedautomatically, for example using a luma key or a chroma key, or may usea predetermined matte, or may be performed by a user through anappropriate graphical user interface, such as a tracing tool that isused by the user to trace a foreground object. A new set of motionvectors is generated using the defined segmentation. A “combination map”also may be generated, as described below in connection with FIG. 4B inone embodiment, to control how the input images are combined using thenew set of motion vectors.

The following description provides three approaches for fixing the setof motion vectors. The particular approach used to remove an artifactmay be selected by providing a mechanism through a user interfacethrough which the user may indicate the kind of artifact that is presentin the image.

The first approach, as shown in the flow chart of FIG. 5A, is used whenthe background segment shows artifacts, but the foreground segment doesnot. In this case, the original motion vectors may be used to describethe foreground motion, but not the background motion. Afterspecification of an image region (step 500) and segmentation of theimage region (step 502), a motion vector for each pixel in thebackground area is determined by running a region tracker on thespecified background area (step 504). Any suitable region tracker, suchas those used for stabilization and object tracking applications may beused. This background area is exclusive of a region (410 in FIG. 4) thatincludes both of the foreground regions FG1 and FG2 of the first andsecond images. The result of the region tracker is a single motionvector describing the motion of the background area. Each pixel in theentire background region, excluding region 410, is then assigned thissingle motion vector, or the parameterized motion model of the tracker(step 506). Next, for each pixel in the bounding box 410, it is thendetermined whether the original motion vector for the pixel, or the newmotion vector for the background is to be used. As shown in FIG. 4A, foreach pixel in the bounding box 410 that incorporates foreground FG1 andforeground FG2, if an original motion vector would move the pixel fromthe foreground region FG1 in the first image to the foreground regionFG2 in the second image (step 510) then the original motion vector isused (step 512). Otherwise, the newly determined motion vector for thebackground is assigned to that pixel (step 514).

Given the modified set of motion vectors, a “combination map,” such asshown in FIG. 4B, may be created (step 516). The combination map may beused to control how pixels from the background and foreground arecombined using the new set of motion vectors. In particular, if a pixelin the bounding box 410 (FIG. 4A), and outside of the foreground FG1 ofthe first input image is transformed by a motion vector to theforeground region FG2 of the second input image, then only the firstinput image is used to generate the output image using this motionvector. Similarly, if a pixel in the foreground region FG1 (FIG. 4A) ofthe first input image is transformed by a motion vector to the regionoutside of the foreground FG2 of the second input image, then only thesecond input image is used to generate the output image using thismotion vector. Thus, each motion vector may be assigned a value, forexample by creating a new two-dimensional image, called a “combinationmap,” which has values of 0, 1, or 2. A value of 0 indicates to combineboth frames A and B, as indicated at 420. A value of 1 indicates thatonly frame A contributes to the output when warping, as indicated at424, and a value of 2 indicates that only frame B contributes to theoutput, as indicated at 422. The combination map may be processed, forexample by a filter, to fill any holes or to account for incorrectlysegmented input regions.

In a second approach, shown in FIG. 5B, the foreground segment exhibitsartifacts, but the background segment does not. In this case, theoriginal motion vectors may be used to describe the background motion,but not the foreground motion. Thus, after segmenting an area intoforeground and background regions (step 530), the background imageregion is cleared (step 532). A tracker is run on the foreground region(step 534) and to obtain a single motion vector or parameterized motionmodel. Next, for each pixel in the bounding box 410, it is determinedwhether the new motion estimate transforms a pixel in the foreground FG1of the first image to a pixel in the foreground FG2 of the second image(step 538). If it does, then the new motion vector obtained from theresult of the tracker is used (step 540). If not, then the originalmotion vector is used (step 542). A combination map then may be created(step 544) to decide from which input images pixels are taken in thewarping operation.

In a third approach, as shown in the flow chart of FIG. 5C, both theforeground and background regions exhibit artifacts. After segmentationof the region (step 550), a region tracker is run on the foregroundregion (step 552). A region tracker is run on the background region(step 556). All pixels in the background BG are assigned this singlemotion vector resulting from the tracker (step 558). Pixels in thebounding box 410 are assigned a motion vector from the foregroundtracker or from the background tracker according to whether the motionvector from the foreground tracker transforms the pixel from foregroundFG1 to foreground FG2 (step 559). A combination map then may be created(step 560).

A user interface also may be provided to allow a user to correct one ormore individual motion vectors. The results of changes to the motionvectors may be shown interactively by updating the output imagegenerated by warping and blending the two input images using the updatedmotion vectors. Another aid in visualizing the result is to show adifference image between warped image 1 and warped image 2. Further, anumber of options may be presented to the user to change the set ofmotion vectors. For instance, a user may be permitted to define a regionof vectors. The user may provide a single value for the whole region, ora separate value for each of several individual pixels in the region.Alternatively, a single value could be assigned automatically to theregion, for example by computing an average value of a different regionof vectors, or other values may be assigned automatically.

A region tracker that may be used in any of the approaches describedabove may produce a single motion vector, which describes translationalmotion, or may produce an affine motion model defined by six parameters,or may produce a projective motion model defined by eight parameters.The output of these motion models is used to generate a new set of perpixel motion vectors.

A general-purpose computer system may be used to implement an embodimentof the invention. Such a computer system typically includes a processor,an input device, a display device, and a memory. The memory storesinterpolation software for generating one or more intermediate imagesbetween two selected images according to the present invention. Thecomputer display device displays a software generated user interface toaccommodate the functionality of the interpolation system.

The computer system may be an IBM compatible personal computer systemwhich is available from a number of computer system manufacturers as iswell known by those of ordinary skill in the art. In another embodiment,the computer system may be a Macintosh computer, available from AppleComputer, Inc. of Cupertino, Calif., a SPARCstation workstation,available from Sun Microsystems of Mountain View, Calif., and aworkstation, available from Silicon Graphics, Inc. of Mountain View,Calif. In a further embodiment of the invention, computer systemexecutes an operating system such as Windows NT by Microsoft Corporationof Redmond, Wash., Solaris by Sun Microsystems, Inc., IRIS by SiliconGraphics, Inc. or versions of Linux, or Unix. Those of ordinary skill inthe art will clearly recognize that other computer systems and operatingsystems are acceptable for practicing the invention, and the inventionis not limited to any particular computer system or operating system.The computer system need only have some type of processor for executinginstructions and manipulating data. The memory stores data andinstructions. The memory may include both a volatile memory such as RAMand non-volatile memory such as a ROM, a magnetic disk, an optical disk,a CD-ROM or the like. The input device allows the user to interact withthe interpolation software. The input device may include, for example,one or more of a keyboard, a mouse, or a trackball. The display devicedisplays a user interface for the interpolation software. The displaydevice may include, for example, a cathode ray tube (CRT), a flat paneldisplay, or some other display device. The interpolation softwareincludes data and computer instructions for generating one or moreintermediate images between two selected images according to the presentinvention.

In one embodiment, the generation of the output images may be performedin a distributed manner using many processors, as shown in FIG. 6. Inparticular, a first processor (CPU1) 600 may be used to compute, asindicated at 602, the optical flow from the first image 604 and secondimage 606 to obtain the motion vectors 608. Because the motion vectorsmay be used to generate all intermediate images, each intermediate image1, 2, . . . , n, can be computed using its own processor 610, 612 . . ., 61N, (CPU1, CPU2 . . . CPUN) with each processor executing its ownwarping software 620, 622, 62N. Thus, each pair of images for whichmotion vectors are computed may be handled independently, possibly withparallel or pipelined instantiations of the system shown in FIG. 6. Thusretiming of a video sequence may be broken down into operations on pairsof images. Motion vectors for each pair of images may be calculatedonce, and may be cached.

There are several applications of these techniques to image processing,including, but not limited to the following.

Retiming can be used to produce slow motion sequences or to alter framerate. New fields or frames can be produced at any point in time betweenexisting frames. Applications include converting 24 frame per secondimage sequences to 50 or 60 interlaced fields per second, converting oldslow frame rate movies to current frame rates (8 fps to 24 fps, forexample), smooth slow motion effects, including super slow motion, andacceleration and deceleration of motion using a curve to specify therate of motion.

The same operations used in retiming can be used to hide jump cuts. Ajump cut occurs when two pieces of material of similar content but shotat slightly different times are adjoined in sequence in a videocomposition, such as shown in FIG. 7. For example, an interview may berecorded as a single sequence of images 700. A segment B might beremoved during editing, so that the sequence resulting from editing(shown at 702) includes a cut from the first segment A to the lastsegment C. When the edited sequence is played back without anyprocessing at the cut from segment A to segment C, the discontinuity atthe cut point may be noticeable and disturbing. Commonly, the cut ishidden by a dissolve transition or a wipe. This cut can be hidden bymorphing between one or more of the last few images of the first segmentA and one or more of the first few images of the subsequent segment C.

There is a “most natural” cadence to a speaker's dialogue, and speakersregularly pause for emphasis or dramatic effect, to think, or for abreath between statements. When two separate audio clips of speech arejoined together to form a new clip, such as at a jump cut, it may bedesirable to introduce a pause between the clips in order to properlypace the speech. Also, with the same audio clip, it may be desirable toextend a pause to change the cadence of the speech. By making changes tothe audio, the corresponding video also is modified to maintainsynchronization between the audio and video. The additional frames usedto extend the video portion of the work may be generated using theoperations described above instead of merely adding redundant frames.Additional video frames may be generated to morph the correspondingvideo to accommodate an extended pause in the audio, as will bedescribed in connection with FIGS. 8A-B. Replacement video frames alsomay be generated to morph the corresponding video to hide the jump cutinstead of using a dissolve or wipe transition at the jump cut, such asdescribed in connection with FIG. 9.

Referring to FIGS. 8A-B, there is shown a video timeline 810 and itscorresponding audio timeline 820. The audio timeline 820 displays therecorded sound wave as time progresses. In FIG. 8A, the audio timelinedisplays a sound wave corresponding to a speaker uttering the words “Iarrived yesterday and I'm planning to stay for a week. Then I'll be offto . . . ” For audio timeline 820, time is measured in seconds, and itis clear that at 6 seconds into the audio clip, the speaker has taken apause before continuing on with speech. If an editor desires to slow thecadence of the speech by extending the pause between the speech, thevideo must also be extended or the audio video portions of the work willlose synchronization. After the new cadence is established, additionalimages are generated to visually blend the abutting video clips at theedit point.

Referring to FIG. 8B, the video timeline 810 and audio timeline 820 areedited to generate an extended pause between the spoken words “and” and“I'm”. The editor trims the abutting video clips surrounding the newlygenerated pause. The operations described above are used to generateadditional images 830 corresponding to the duration of the pause, asshown in FIG. 8C.

Speech pauses in the audio track are easily detectable and can serve asa way to automatically identify the boundary points for the additionalimages. In particular, the first instances of audio above a selectedthreshold that immediately precede and follow an edit point may beidentified as the boundary points for the additional images. In thismanner the start and end images for blending the video during the pauseare easily identified.

Optical flow based morphing also can be used to generate a transition ata jump cut or even between two dissimilar pieces of video. In this casethe operations described above are applied between pairs of imagesselected from the incoming and outgoing video. Referring to the FIG. 9,this effect determines the motion vectors between images A1 and B5, andwarps and blends the corresponding images. Next the motion vectorsbetween images A2 and B5 are determined, and the corresponding imagesare warped and blended. The same process continues for each pair ofimages until the motion vectors for images A5 and B5 are determined andused to warp and blend the corresponding images. The factor that is usedto scale the motion vectors and to blend the warped images for each pairof images is proportional to the number of frames into the effect atwhich the output image is produced. The result is that for the firstoutput image, image A1 is only slightly warped toward image B5, andimage B5 is heavily warped toward image A1, but the warped image A1contributes to the output image more than the warped image B5. At thelast output image, input image A5 is heavily warped toward image B5, andimage B5 is only slightly warped toward image A5, but the warped imageB5 contributes to the output image more than the warped image A5. Forinterlaced video, only the first field of image B5 is used. The fieldsof the input image sequence are scaled up to full frame size and warpedto a scaled up field of image B5 to compute the appropriate outputfield.

Motion vectors also may be used to selectively blur an image in thedirection of motion to add motion blur. Conversely, the motion-basedwarp may be used to align multiple frames to remove motion blur.

Visual defects such as film scratches and video dropouts may also beidentified using frame differencing or a gray scale morphologicalfilter. An area that contains a defect may be filled using motion basedwarping. Because the motion vectors generally cannot be calculateddirectly in the area of the defect, they can be estimated using the twoframes on either side of the one with the defect. Vectors also may becomputed for the region near, but outside, the defect and propagated viasmoothing to the interior of the defective region.

Motion compensated interpolation also may be used to change the durationof a sequence of images and its associated audio. Such an operation maybe provided for selection by an operator of the interpolation softwarein a manner that selection of the operation automatically adjusts theduration of both the sequence of images and audio, without having toseparately process the audio. The operator also may input an indicationof a desired duration of the sequence of images. In this application,for each pair of images, a motion vector is computed for each pixel thatdescribes motion of the pixel between the two images. Motion compensatedinterpolation is performed to generate one or more images between thetwo images according to the determined motion vectors. Suchinterpolation may be performed for multiple pairs of images to createthe output sequence of images. The duration of the associated audio thenis adjusted to retain synchronization with the output sequence ofimages. The adjustment of the duration may be performed usingresampling, which changes the pitch of the audio. The adjustment of theduration may be performed using time scaling, which does not change thepitch of the audio. The operation is useful in various applications suchas, when the sequence of images is processed to be a slow motionsequence, or when the sequence of images is processed to fit apredetermined amount of time allotted for it in a production.

Optical flow also can be used to create a mapping from one twodimensional data set to another. As long as it is reasonable to assumethat there is a conservation of a quantity that is analogous toluminance in the two data sets, then the results will be meaningful.That is, analyzing motion within the two data sets using optical flowwill indicate how data points in the one data set move to points in theother data set. One such application is the automatic generation ofsecondary color correction maps by applying optical flow to twotwo-dimensional color histograms. For example, there may be two relatedsequences (e.g., two different camera angles of the same scene) forwhich color correction may be performed. One or more images for eachsequence may be used to generate a color histogram for each sequence. Acolor histogram of an image indicates the number of pixels in the imagefor each color, such as each pair of Cr,Cb values. The histogram countvalues are analogous to luminance values in this application and areassumed to be conserved between the two histograms. The color histogramsmay be filtered, for example using a median filter, or a Guassian orother blurring filter before being analyzed for motion. Motion of databetween the two histogram data sets indicates a change of color ofobjects in the scene. A set of motion vectors then is calculated todescribe the motion between the histogram of the first sequence and thehistogram of the second sequence. Thus, the motion vectors so determinedindicate, for each pair of Cr, Cb values, another Cr, Cb value to whichit maps. This mapping may be used to load a map for secondary colorcorrection to allow one or more images in one of the sequences, or inanother sequence, to have colors corrected to match one or more imagesin the other sequence.

Having now described a few embodiments, it should be apparent to thoseskilled in the art that the foregoing is merely illustrative and notlimiting, having been presented by way of example only. For example, theoutput image need not be spaced temporally between the two images fromwhich it is created. Numerous modifications and other embodiments arewithin in the scope of one of ordinary skill in the art and arecontemplated as falling within with scope of the invention.

What is claimed is:
 1. A method for processing two fields of interlacedvideo, comprising: computing motion vectors describing motion of imagecharacteristics from a field to another field of opposite sense;removing from the motion vectors an offset corresponding to one half ofa line and having a sign according to an orientation of the y-axis ofthe image space and which field includes the top line; using the motionvectors to generate a sampling region at a desired output time;transforming the sampling region using the motion vectors to a sampletime at one of the fields; transforming the sampling region using themotion vectors to a sample time at the other of the fields; determininga field sense of an output field to be generated at the desired outputtime; translating the transformed sampling region for the field with afield sense opposite the field sense of the output field by an offset ofone half of a line and having a sign determined by an orientation of they-axis of the image space and which field includes the top line; andgenerating the output field using the transformed and translatedsampling regions and the input fields.
 2. The method of claim 1, furthercomprising: wherein the desired output time is the time of one of thefields; combining the generated output field with the field at thedesired output time to generate a progressive image.
 3. The method ofclaim 2, further comprising: performing an effect on the progressiveimage.
 4. The method of claim 3, further comprising: verticallydecimating the progressive image with the effect to produce a field atthe desired output time.
 5. A method for processing two fields ofinterlaced video, comprising: computing motion vectors describing motionof image characteristics from a field to another field of oppositesense; removing from the motion vectors an offset corresponding to onehalf of a line and having a sign according to an orientation of they-axis of the image space and which field includes the top line;selecting a time of one of the fields as a desired output time;transforming a sampling region specified at the selected time using themotion vectors to a sample time at the field that is being warped;translating the transformed sampling region by an offset of one half ofa line and having a sign determined by an orientation of the y-axis ofthe image space and which field includes the top line; and generatingthe output field at the desired output time using the transformed andtranslated sampling region and the field that is being warped.
 6. Themethod of claim 5, further comprising: combining the generated outputfield with the field at the desired output time to generate aprogressive image.
 7. The method of claim 6, further comprising:performing an effect on the progressive image.
 8. The method of claim 7,further comprising: vertically decimating the progressive image with theeffect to produce a field at the desired output time.
 9. The method ofclaim 6, further comprising: exporting the progressive image to a file.10. The method of claim 6, further comprising: displaying theprogressive image as a still frame.
 11. The method of claim 10, whereindisplaying the progressive image as a still frame includes displayingthe progressive image in a freeze frame effect.
 12. The method of claim10, wherein displaying the progressive image as a still frame includesdisplaying the progressive image upon stopping playback.
 13. The methodof claim 5, further comprising: warping another field of the oppositesense to the desired output time; and blending the two warped fields toproduce a field at the desired output time.